"Lumen Technologies says that its Multi-Cloud Gateway (MCGW) - which it is deploying across its network in major U.S. markets - will meet the challenge of moving artificial intelligence (AI)-generated data quickly and securely across clouds, data centers, and distributed locations. The MCGW, an element of the company's shift to cloud-based telecom, is a software-defined self-service routing layer on Lumen's global fiber network. It provides private connectivity among clients, which include enterprises, hyperscalers, and emerging cloud platforms."
"Telecompetitor reached out to Lumen to ask how smaller providers might approach the reality of AI traffic in their networks. "AI traffic doesn't just require more capacity; it requires smarter control. For smaller providers, the opportunity isn't to replicate hyperscale infrastructure, but to evolve how networks are designed and operated. AI workloads are inherently distributed, and architectures built for static, point‑to‑point connectivity will be increasingly stressed," Lumen Technologies Vice President, Digital Strategy & Excellence David Shacochis told Telecompetitor."
Lumen Technologies is deploying a Multi-Cloud Gateway (MCGW) across major U.S. markets to move AI-generated data quickly and securely among clouds, data centers, and distributed locations. The MCGW is a software-defined, self-service routing layer on a global fiber network that provides private connectivity for enterprises, hyperscalers, and emerging cloud platforms. Target sectors include financial services, retail, healthcare, and manufacturing. The platform converts traditional telecom interconnections into programmable cloud fabrics, enabling dynamic cloud-to-cloud and cloud-to-enterprise connections, optimizing traffic for performance and cost, and supporting AI workload distribution and real-time data exchange. Smaller providers should modernize design, increase automation, and prioritize predictable private connectivity to scale and manage costs.
Read at Telecompetitor
Unable to calculate read time
Collection
[
|
...
]